Exceptional Model Mining

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Description

In most databases, it is possible to identify small partitions of the data
where the observeddistribution is notably different from that of the
database as a whole. In classical subgroup discovery, one considers
the distribution of a single nominal attribute, and exceptional subgroups
show a surprising increase in the occurrence of one of its values.
In this talk, I'll introduce Exceptional Model Mining (EMM), a framework
that allows for more complicated target concepts. Rather than finding
subgroups based on the distribution of a single target attribute,
EMM finds subgroups where a model fitted to that subgroup is somehow
exceptional. I'll discuss regression as well as classification models,
and define quality measures that determine how exceptional a given
model on a subgroup is. Our framework is general enough to be applied
to many types of models, even from other paradigms such as
association analysis and graphical modeling.

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